On the Trend Recognition and Forecasting Ability of Professional Traders

34 Pages Posted: 27 Jun 2003

See all articles by Markus Glaser

Markus Glaser

Ludwig Maximilian University of Munich (LMU) - Faculty of Business Administration (Munich School of Management)

Martin Weber

University of Mannheim - Department of Banking and Finance

Thomas Langer

University of Muenster - Finance Center

Multiple version iconThere are 3 versions of this paper

Date Written: May 2003

Abstract

Empirical research documents that temporary trends in stock price movements exist. Moreover, riding a trend can be a profitable investment strategy. Thus, the ability to recognize trends in stock markets influences the quality of investment decisions. In this Paper, we provide a thorough test of the trend recognition and forecasting ability of financial professionals who work in the trading room of a large bank and novices (MBA students). In an experimental study, we analyse two ways of trend prediction: probability estimates and confidence intervals. Subjects observe stock price charts, which are artificially generated by either a process with positive or negative trend and are asked to provide subjective probability estimates for the trend. In addition, the subjects were asked to state confidence intervals for the development of the chart in the future. We find that depending on the type of task either underconfidence (in probability estimates) or overconfidence (in confidence intervals) can be observed in the same trend prediction setting based on the same information. Underconfidence in probability estimates is more pronounced the longer the price history observed by subjects and the higher the discriminability of the price path generating processes. Furthermore, we find that the degree of overconfidence in both tasks is significantly positively correlated for all experimental subjects whereas performance measures are not. Our study has important implications for financial modelling. We argue that the question which psychological bias should be incorporated into a model does not depend on a specific informational setting but solely on the specific task considered. This Paper demonstrates that a theorist has to be careful when deriving assumptions about the behaviour of agents in financial markets from psychological findings.

Keywords: Trend recognition, forecasting, conservatism, overconfidence, professionals, financial modelling

JEL Classification: C90, G10

Suggested Citation

Glaser, Markus and Weber, Martin and Langer, Thomas, On the Trend Recognition and Forecasting Ability of Professional Traders (May 2003). Available at SSRN: https://ssrn.com/abstract=420460

Markus Glaser

Ludwig Maximilian University of Munich (LMU) - Faculty of Business Administration (Munich School of Management) ( email )

Schackstra├če 4
Munich, 80539
Germany

Martin Weber (Contact Author)

University of Mannheim - Department of Banking and Finance ( email )

D-68131 Mannheim
Germany
+49 621 181 1532 (Phone)
+49 621 181 1534 (Fax)

Thomas Langer

University of Muenster - Finance Center ( email )

Universitatsstr. 14-16
Muenster, 48143
Germany
+49 251 83 22033 (Phone)

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
32
Abstract Views
1,833
PlumX Metrics